Reverse simulation method and platform for dynamic operation of power system of electric vehicles

Abstract

This invention discloses a reverse simulation method and platform for the dynamic operation of an electric vehicle's powertrain. The method includes building a physical simulation model of the electric vehicle's powertrain, including a charging model, a temperature model, a battery model, a vehicle dynamics model, and an energy transfer model. Injecting collected real-world driving data into the model allows for rapid reverse simulation of the energy transfer, consumption, and battery degradation of an electric vehicle over a long period of real-world driving. This method enables electric vehicle consumers and manufacturers to quickly simulate and evaluate the vehicle's energy transfer process and the impact of vehicle usage factors on energy consumption and battery life.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy electric vehicle power system modeling and performance evaluation, and in particular to a reverse simulation method and a simulation platform for the dynamic operation of a power system of an electric vehicle. Background Art

[0002] Existing methods for assessing the capacity degradation of electric vehicle (EV) batteries are mostly based on accelerated lithium battery degradation experiments, including charge and discharge cycle testing, electrochemical modeling, and data-driven approaches. However, few methods quantify the impact of actual driver behavior on battery degradation, making it difficult to accurately guide EV users in optimizing their EV usage to extend battery life.

[0003] There are many current automotive simulation methods, but there is a lack of simulation methods specifically for electric vehicle power systems, especially methods that can simulate and predict the energy transfer and battery degradation of different electric vehicles over long periods of time in a short period of time. Summary of the Invention

[0004] In order to at least address one of the deficiencies in the prior art, the present invention provides a reverse simulation method for the dynamic operation of a power system for electric vehicles and a simulation platform thereof, which can quantify the impact of driver operating factors on the energy consumption and battery degradation of electric vehicles over a long period of time in a short period of time. Specifically, by establishing a physical model of the electric vehicle power system and simulating the transfer of electrical energy, thermal energy and mechanical energy during vehicle driving, the current and battery temperature information can be calculated in real time, thereby calculating the battery calendar aging rate and thermal aging rate, and thus calculating the battery capacity degradation and other conditions.

[0005] To achieve the purpose of the present invention, the present invention provides a reverse simulation method for the dynamic operation of a power system of an electric vehicle, comprising the following steps:

[0006] Build a physical simulation model of the electric vehicle power system to reflect the process of energy flow and conversion of the electric vehicle. The physical simulation model of the electric vehicle power system includes:

[0007] Automobile dynamics model, used to calculate the total force acting on the vehicle;

[0008] The energy transfer model includes an electric vehicle braking energy recovery module, a driving current calculation module, and a driving power calculation model. The electric vehicle braking energy recovery module is used to start and stop braking energy recovery, the driving current calculation module is used to calculate the driving current of the electric vehicle, and the driving power calculation model is used to calculate the driving power of the electric vehicle.

[0009] Temperature model, including the electric vehicle heating, ventilation and air conditioning system model, the battery thermal management model, the cabin temperature model, and the battery temperature model. The electric vehicle heating, ventilation and air conditioning system model is used to calculate the power consumed by the heating, ventilation and air conditioning system. The battery thermal management model is used to calculate the power required for battery heating or cooling. The cabin temperature model is used to calculate the cabin temperature. The battery temperature model is used to calculate the battery temperature.

[0010] Battery model, including battery capacity degradation model and battery real-time SOC calculation model. The battery capacity degradation model is used to calculate the battery calendar aging rate and thermal aging rate, thereby calculating the battery capacity degradation. The battery real-time SOC calculation model is used to calculate the battery real-time SOC;

[0011] The charging model includes a charging judgment module, a charger selection model, and a charging power and charging current model. The charging judgment module is used to calculate the dwell time based on driving data to determine whether there is sufficient time for charging during the day's trip. The charger selection model is used to select car chargers of different power levels. The charging power and charging current model is used to calculate the charging current based on the charging power and charging efficiency.

[0012] Based on the driving data, the energy transfer of the electric vehicle power system is simulated through the electric vehicle power system physical simulation model to obtain simulation results, which include but are not limited to changes in cabin temperature, battery pack temperature, SOC and battery capacity degradation.

[0013] Furthermore, in the vehicle dynamics model, the formula for calculating the total force on the vehicle is:

[0014] F pt =F d +F r +F g +F a

[0015]

[0016] Among them, F pt The total force required to drive the electric vehicle to move, F d is the air resistance, F r is the rolling resistance, F g is the slope resistance, F a is the acceleration resistance, W pt , P pt Divided into the energy required to drive the electric vehicle and the total power, v c (t) is the speed of the electric vehicle, d is the drag, and t is the time.

[0017] Furthermore, in the energy transfer model, the electric vehicle braking energy recovery module is used to start braking energy recovery when the vehicle speed is higher than a preset value and decelerates, and at a constant braking energy recovery efficiency f rbs Recover powertrain energy into the battery system;

[0018] The formula for calculating the total power of an electric vehicle when it is running is:

[0019] P bat =P pt +P hvac +P btms +P rbs

[0020] Among them, P hvac The power consumption of the heating, ventilation and air conditioning system for electric vehicles, P btms is the power consumed by the battery heating system, P rbs It is the braking energy recovery power;

[0021] The formula for calculating the driving current is:

[0022] P bat =(OCV+I c ·R bat )·I c

[0023] Where OCV is the open circuit voltage, R bat is the internal resistance, I c Input / output current of the battery pack.

[0024] Furthermore, in the temperature model, when the electric vehicle is running, the battery temperature is:

[0025]

[0026] Among them C bat is the battery heat capacity, T bat is the battery temperature, T a is the ambient temperature, T c is the cab temperature, K ab , K bc , K btms is the heat transfer coefficient, Q btms is the heat dissipation / heating energy of the battery pack thermal management system, Q bat is the heat energy of the battery pack, T b,up , T b,low For battery management, the highest and lowest temperatures, min(T bat -T b，up , 10) refers to T bat -T b，up Or the smallest value among 10, min(T b，low-T bat , 10) refers to T b，low -T bat Or the smallest value among 10;

[0027]

[0028] Among them C c is the specific heat capacity of the cockpit, K ac is the heat transfer coefficient, Q hvac Energy consumed by heating, ventilation and air conditioning systems for electric vehicles, COP cooling , COP heating is the heat dissipation and heating electric energy coefficient.

[0029] Furthermore, in the battery model, the real-time SOC of the electric vehicle is:

[0030]

[0031] Among them, SOC0 is the initial SOC value of the battery pack, C bat,r The remaining rated capacity of the battery pack;

[0032] The remaining capacity of the battery pack, i.e. the battery pack capacity life calculation formula is:

[0033] C bat,r =C baa,ini τ a τ c

[0034]

[0035] Among them, C baa,ini is the initial capacity of the battery pack, τ a is the thermal aging rate of the battery pack, τ c is the calendar aging rate of the battery pack, σ fcn Battery aging degradation severity factors, α, β, η, is the battery aging coefficient, E a is the activation energy, R g is the universal gas constant, Q acc It is the accumulated ampere-hour.

[0036] Furthermore, in the charger selection model, the types of chargers include: primary charging, secondary charging, DC fast charging, and ultra-fast charging.

[0037] The present invention provides a reverse simulation platform for the dynamic operation of the power system of electric vehicles. The simulation platform collects or simulates real daily driving data and uses the aforementioned method to perform reverse simulation. The real daily driving data includes but is not limited to: data collection time and its corresponding vehicle speed, road slope, ambient temperature, and vehicle running / stop status. The platform can perform cyclic long-term simulation based on the above driving data.

[0038] Obtain the parameters and information required for modeling and simulation; based on the modeling parameters, build a physical simulation model of the electric vehicle's powertrain. During the simulation, configure the charging and driving modes, primarily selecting the charger type and enabling or disabling certain functions. Then, inject the collected real-world driving data into the model, allowing for rapid reverse simulation to simulate the energy transfer, consumption, and battery degradation of an electric vehicle over a long period of time.

[0039] Furthermore, the platform can be used to customize vehicle performance and appearance parameters, battery parameters, and charger parameters to simulate vehicles of different sizes and models.

[0040] Furthermore, a driving mode configuration can be selected, including: battery thermal management system on / off, heating, ventilation and air conditioning system on / off, and brake energy recovery system on / off.

[0041] Furthermore, the platform simulation period can be customized to simulate the degradation of electric vehicle power batteries over a long period of time or even the entire life cycle in a shorter period of time.

[0042] Furthermore, the platform obtains the parameters required: according to the model simulated by the user, the specific model appearance parameters and performance parameters of the model are obtained, and the user can input the above parameters into the platform; at the same time, the user can collect driving data through the actual vehicle, or generate driving condition data through typical working conditions (the driving data collected by the actual vehicle is in the same format as the driving condition data. The former can be understood as the real vehicle speed and other data collected every day through the platform, and the latter can be understood as the simulated driving speed and other data artificially generated through typical driving conditions such as NEDC and WLTC. The two are just different in the acquisition channels and content, but the purpose and format are the same). The driving data required by the platform include: data collection time, vehicle speed, road slope, ambient temperature and vehicle running / stop status; the acquired driving data is organized into an Excel driving document. The Excel example of the driving document is as follows Figure 2 As shown, the driving document data is stored in the unified DayTrips file directory of the algorithm file, and the driving data will be automatically retrieved when the platform is running.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. This invention proposes a reverse simulation method and platform for the dynamic operation of the power system of electric vehicles. Compared with existing electric vehicle simulation platforms, the simulation platform designed by this invention can quantify the impact of different driver usage factors on battery capacity and driving energy consumption (this invention can quantify the impact of different usage factors by controlling variables, such as always selecting Level_1 for the first simulation and Level_2 for the second simulation, and comparing the final results). This can guide electric vehicle users in optimizing the use of electric vehicles.

[0045] 2. The electric vehicle simulation platform proposed in this invention, by importing real-world driving data and a user-defined simulation period, can quickly quantify the impact of different usage factors on electric vehicle energy transfer and battery degradation over long periods of time, even over the entire lifecycle. (For example, by repeatedly running a year's worth of driving data over, say, 10 years or longer, the computer can quickly complete the calculations, allowing for quantification of long-term impacts.)

[0046] 3. This invention can quantify the impact of different chargers on battery capacity degradation by integrating charging models (calculating the cumulative ampere-hours and other data required for the battery capacity and life model through the vehicle dynamics model and the energy transfer model, and calculating the temperature required for the battery capacity and life model through the temperature model, that is, calculating the input of the battery capacity and life model through each sub-model of the power system, thereby calculating the battery capacity / life and quantifying degradation);

[0047] 4. The present invention can quantify the impact of the above systems on the energy consumption and battery degradation of electric vehicles by allowing users to customize whether the electric vehicle brake energy recovery module is turned on, whether the battery thermal management model in the temperature model is turned on, and whether the electric vehicle heating, ventilation and air-conditioning system model is turned on (on: calculate the heat dissipation and heating amount according to the above formula to adjust the temperature; off: both the heat dissipation and heating amount are 0). BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 The figure shows a reverse simulation method for dynamic operation of a power system and a software platform framework diagram thereof in an embodiment of the present invention.

[0049] Figure 2 Shown is an example diagram of a driving document in an embodiment of the present invention.

[0050] Figure 3 Shown is a flowchart of the specific implementation steps of the reverse simulation method for dynamic operation of a power system and its software platform in an embodiment of the present invention.

[0051] Figure 4 The figure shows a comparison of the effects of Level 1 charging and DC fast charging on battery capacity over a ten-year period.

[0052] Figure 5 Shown is a comparison of the impact of brake energy recovery / battery pack thermal management system / heating, ventilation and air conditioning system on battery capacity within one year.

[0053] Figure 6 Schematic diagram of the charger types and their parameters set for the platform.

[0054] Figure 7 Schematic diagram of the vehicle appearance and performance parameters set by the platform by default. DETAILED DESCRIPTION

[0055] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without making creative efforts should fall within the scope of protection of the present invention.

[0056] The present invention provides a reverse simulation method for the dynamic operation of a power system of an electric vehicle, comprising the following steps:

[0057] Build a physical simulation model of the electric vehicle power system, which includes:

[0058] Automobile dynamics model, used to calculate the total force acting on the vehicle;

[0059] The energy transfer model includes an electric vehicle braking energy recovery module, a driving current calculation module, and a driving power calculation model. The electric vehicle braking energy recovery module is used to start and stop braking energy recovery, the driving current calculation module is used to calculate the driving current of the electric vehicle, and the driving power calculation model is used to calculate the driving power of the electric vehicle.

[0060] Temperature model, including the electric vehicle heating, ventilation and air conditioning system model, the battery thermal management model, the cabin temperature model, and the battery temperature model. The electric vehicle heating, ventilation and air conditioning system model is used to calculate the power consumed by the heating, ventilation and air conditioning system. The battery thermal management model is used to calculate the power required for battery heating or cooling. The cabin temperature model is used to calculate the cabin temperature. The battery temperature model is used to calculate the battery temperature.

[0061] Battery model, including battery capacity degradation model and battery real-time SOC calculation model. The battery capacity degradation model is used to calculate the battery calendar aging rate and thermal aging rate, thereby calculating the battery capacity degradation. The battery real-time SOC calculation model is used to calculate the battery real-time SOC;

[0062] The charging model includes a charging judgment module, a charger selection model, and a charging power and charging current model. The charging judgment module is used to calculate the dwell time based on driving data to determine whether there is sufficient time for charging during the day's trip. The charger selection model is used to select car chargers of different power levels. The charging power and charging current model is used to calculate the charging current based on the charging power and charging efficiency.

[0063] Based on the driving data, the energy transfer of the electric vehicle power system is simulated through the electric vehicle power system physical simulation model to obtain simulation results, which include but are not limited to changes in cabin temperature, battery pack temperature, SOC and battery capacity degradation.

[0064] The vehicle dynamics model is used to calculate the total force required for the vehicle to run, taking into account the rolling resistance, climbing resistance, acceleration resistance, and air resistance experienced by the vehicle during driving. The specific calculation formula is:

[0065] F pt =F d +F r +F g +F a

[0066]

[0067] Among them F pt The total force required to drive the electric vehicle to move, F d is the air resistance, F r is the rolling resistance, F g is the slope resistance, F a is the acceleration resistance, W pt , P pt Divided into the energy required to drive the electric vehicle and the total power, v c (t) is the speed of the electric vehicle, d is the drag in the air drag force, d is the drag, and t is the time.

[0068] In the energy transfer model, for the braking energy recovery strategy, it is set that when the vehicle speed is higher than 5km / h and deceleration is in progress, braking energy recovery is turned on and the braking energy recovery efficiency is constant. rbs Recover the powertrain energy into the battery system, and the braking energy recovery power P rbs for:

[0069] P rbs =P pt ·f rbs

[0070] The total power of an electric vehicle when running is:

[0071] Pbat =P pt +P hvac +P btms +P rbs

[0072] Among them, P hvac The power consumption of the heating, ventilation and air conditioning system for electric vehicles, P btms Power consumed by the battery heating system.

[0073] The relationship between current and power when an electric vehicle is running is:

[0074] P bat =(OCV+I c ·R bat )·I c

[0075] Where OCV is the open circuit voltage, R bat is the internal resistance, I c Input / output current of the battery pack.

[0076] The temperature model mainly simulates the temperature changes and energy transfer process of the electric vehicle cab and battery pack.

[0077] In the temperature model, the battery temperature is calculated as follows:

[0078]

[0079] Among them C bat is the battery heat capacity, T bat is the battery temperature, T a is the ambient temperature, T c is the cab temperature, K ab , K bc , K btms is the heat transfer coefficient, Q btms is the heat dissipation / heating energy of the battery pack thermal management system, Q bat is the heat energy of the battery pack, T b,up , T b,low The maximum and minimum temperatures for battery management set by the platform. Users can customize their values ​​in the platform. min(T bat -T b，up , 10) refers to T bat -T b，up Or the smallest value among 10, min(T b，low -Tbat,10) refers to the minimum value among Tb, low-Tbat or 10.

[0080]

[0081] Among them C cis the specific heat capacity of the cockpit, K ac is the heat transfer coefficient, Q hvac The heating, ventilation and air conditioning system of electric vehicles consumes energy. The heating, ventilation and air conditioning system of electric vehicles consumes power P hvac In some embodiments of the present invention, the maximum cooling power is set to 4kW and the maximum heating power is set to 4.5kw; COP cooling , COP heating is the heat dissipation and heating electric energy coefficient.

[0082] The battery model includes a battery capacity degradation model, i.e., a battery capacity life model, and a battery real-time SOC calculation model. The battery capacity degradation model is used to calculate the battery calendar aging rate and thermal aging rate, thereby calculating the battery capacity degradation, i.e., the battery life. The real-time SOC of the electric vehicle is:

[0083]

[0084] Where SOC0 is the initial SOC value of the battery pack, C bat,r The remaining rated capacity of the battery pack.

[0085] The present invention takes into account both calendar aging and thermal aging of the power battery. The remaining capacity of the battery (pack), i.e., the capacity life of the battery (pack), is calculated as follows:

[0086] C bat,r =C baa,ini τ a τ c

[0087]

[0088] Among them, C baa,ini is the initial capacity of the battery pack, τ a is the thermal aging rate of the battery pack, τ c is the calendar aging rate of the battery pack, which can be obtained through user-defined input or the platform's embedded battery calendar aging coefficient table, σ fcn Battery aging degradation severity factors, α, β, η, The battery aging coefficient set by the platform, E a is the activation energy, R g is the universal gas constant, Q acc It is the accumulated ampere-hour.

[0089] The charging model can simulate the energy transfer and battery aging of electric vehicles when charging. Users can use this charging model to simulate and evaluate the impact of different chargers on electric vehicles.

[0090] In the charging model, the charger selection model can select car chargers of different powers according to the user's settings before simulation. The charging power and charging current model can calculate the charging current based on the charging power and charging efficiency of the charger selected by the user:

[0091] I chg =P chg *E chg / V chg

[0092] Among them, I chg is the charging current, E chg is the charging efficiency, V chg is the charging voltage.

[0093] In some embodiments of the present invention, four charging types are set, including primary charging, secondary charging, DC fast charging, and ultra-fast charging, and users can set and change the above information in the EV_DOS file.

[0094] The present invention also provides a reverse simulation platform for the dynamic operation of the power system of electric vehicles. The simulation platform collects or simulates real daily driving data and performs reverse simulation using the method described in any one of claims 1 to 6. The real daily driving data includes but is not limited to: data collection time and its corresponding vehicle speed, road slope, ambient temperature, and vehicle running / stop status. The platform can perform cyclic long-term span simulation based on the above driving data.

[0095] The platform allows users to customize vehicle performance and appearance parameters, battery parameters, and charger parameters to simulate vehicles of different sizes and models.

[0096] The present invention allows for selectable driving mode configurations, specifically including: battery thermal management system on / off, heating, ventilation, and air conditioning system on / off, and brake energy regeneration system on / off. In some embodiments of the present invention, users can configure the EV charger type and the total number of simulated vehicle years in the EV_DOS file. They can also configure whether the EV's brake energy regeneration is enabled, whether the battery pack thermal management system is enabled, and whether the heating, ventilation, and air conditioning system model is enabled, thereby enabling users to simulate the impact of different driving conditions on the EV.

[0097] The platform simulation period can be customized to simulate the degradation of electric vehicle power batteries over a long period of time or even the entire life cycle in a relatively short period of time.

[0098] The charging model can calculate the daily charging time based on the driving data input by the user. In the platform, based on the charging mode selected by the user, it simulates the energy transfer of the electric vehicle power system through the electric vehicle power system physical simulation model, and restores the changes in cockpit temperature, battery pack temperature, SOC and battery capacity degradation.

[0099] With the above settings, the platform can generate an Excel file of simulation results in the same folder as the program. Users can read the remaining value of the battery rated capacity, daily energy consumption of the vehicle, cumulative mileage, cumulative driving time, cumulative charge and discharge capacity, cumulative charging energy, cumulative charging price, and cumulative charging time data in Excel.

[0100] The effectiveness of the present invention is verified by using specific examples below.

[0101] Example 1: The platform of the present invention is used to quantify the impact of using only Level 1 charging (charging power set to 1.8kW, charging voltage set to 120V, charging efficiency set to 0.85) and only DC fast charging (charging power set to 60kW, charging voltage set to 480V, charging efficiency set to 0.85) on the capacity degradation of electric vehicle batteries over a period of 10 years.

[0102] Step 1: The user opens the folder where the software platform is located and puts the set one-year driving data into the "DayTrips" folder. This embodiment 1 uses the driving document data set by the platform by default. The driving document data example is as follows: Figure 2 As shown in Table 2, the vehicle appearance and performance parameters use the default parameters set by the platform.

[0103] Step 2: The user opens the software platform and sets the charger type chargetype to "Level_1" (i.e., first-level charging) in the file named EV-DOS, sets the electric vehicle braking energy recovery to be turned on, the battery pack thermal management system to be turned on, the heating, ventilation and air conditioning system to be turned on, and sets the simulation period to 10 years.

[0104] Step 3: Click Run, refer to Figure 3 The platform will automatically initialize parameters, import the driving data files placed by the user in "DayTrips" into the simulation platform, and automatically read the number of driving files / simulation days. When the number of simulation days is less than the number of days of loaded driving data, the driving data of each day will be simulated accordingly.

[0105] Step 4: Going further, based on the total daily travel time obtained by importing the single-day driving data, determine whether to continue the simulation. When the cumulative simulation time is less than the total daily travel time, determine whether the battery SOC is lower than 0.1. When it is lower than 0.1, the platform automatically enters the charging mode; when the SOC is not lower than 0.1, determine whether the vehicle is running. When the vehicle is not running, the dwell time is accumulated; when the vehicle is running, the power consumed by the heating, ventilation and air-conditioning system and the battery thermal management system, the open circuit voltage OCV, the battery pack internal resistance, the battery power and the current are calculated respectively through the established electric vehicle power system physical simulation model, and the real-time SOC, the consumed energy, the accumulated ampere-hours and the temperature of the cockpit and the battery are calculated. Finally, the remaining rated capacity of the battery pack is calculated every 60 seconds.

[0106] Step 5: When the cumulative simulation time is greater than the total single-day travel time, enter the single-day charging simulation. When the cumulative stay time is greater than 30 minutes and the SOC is less than 0.8, the power consumed by the heating, ventilation and air-conditioning system and the battery thermal management system, the open circuit voltage OCV, the battery pack internal resistance, the battery power and the current are calculated through the established electric vehicle power system physical simulation model. The real-time SOC, the consumed energy, the cumulative ampere-hours and the temperature of the cockpit and the battery are calculated. Finally, the remaining rated capacity of the battery pack is calculated every 60 seconds.

[0107] After each day's driving data is processed through steps 4 and 5 above, determine whether the cumulative number of simulated years has reached the set cumulative number of simulation years. If not, continue with steps 4 and 5 until the set number of years is reached. The program automatically stops and outputs the simulation result Excel data in the same file. In the simulation result Excel, users can view the specific data of the electric vehicle battery capacity degradation each day when charging with a first-level charger.

[0108] Step 6: Open the software platform and, in the file named EV-DOS, set the charger type to "DC_Fast," enable the electric vehicle's brake energy recovery, the battery pack thermal management system, and the heating, ventilation, and air conditioning systems, and set the simulation duration to 10 years. Click Run, and the platform will repeat steps 3 through 5. The program will automatically stop and output the simulation results in Excel format to the same file. In this Excel file, users can view detailed data on the daily battery capacity degradation of the electric vehicle when charging with a DC fast charger.

[0109] After the above steps, a comparison chart of the effects of primary charging and DC fast charging on battery capacity degradation is obtained after 10 years. The comparison chart is as follows: Figure 4As shown in the figure, the simulation platform shows that the capacity of the primary charging method decays more slowly, while the capacity of the DC fast charging method decays 9% more after ten years. The above simulation took less than 8 hours in total. As shown in Example 1, the platform can simulate the impact of different charger types on the battery life of electric vehicles after 10 years in just one day.

[0110] Example 2: Using the platform of the present invention to quantify the impact of the brake energy recovery system, heating, ventilation and air conditioning system, and battery thermal management system on battery capacity degradation over a period of one year:

[0111] Step 1: The user opens the folder where the software platform is located. In this embodiment 2, the driving document data (one year's driving data) set by the platform by default is used. The example of driving document data is as follows: Figure 2 As shown in Figure 2, the set one-year driving data is placed in the "DayTrips" folder, and the vehicle appearance and performance parameters use the default parameters set by the platform (the platform default data is set by a pure electric vehicle model by default on the platform, which can be obtained by searching the specific parameter table on the web page and references, so users can also change these parameters according to the model they need to simulate), as shown in Table 2.

[0112] Step 2: The user opens the software platform and sets the charger type chargetype to "DC_Fast" in the file named EV-DOS. The user also sets the electric vehicle braking energy recovery to be turned on, the battery pack thermal management system to be turned off, the heating, ventilation and air conditioning systems to be turned off, and the simulation period to be 1 year.

[0113] Step 3: Click Run, refer to Figure 3 The platform will automatically initialize parameters, import the driving data files placed by the user in "DayTrips" into the simulation platform, and automatically read the number of driving files / simulation days. When the number of simulation days is less than the number of days of loaded driving data, the driving data of each day will be simulated accordingly.

[0114] Step 4: Based on the total daily travel time obtained by importing the single-day driving data, determine whether to continue the simulation. When the cumulative simulation time is less than the total daily travel time, determine whether the battery SOC is lower than 0.1. When it is lower than 0.1, the platform automatically enters the charging mode; when the SOC is not lower than 0.1, determine whether the vehicle is running. When the vehicle is not running, the dwell time is accumulated; when the vehicle is running, the power consumed by the heating, ventilation and air-conditioning system and the battery thermal management system, the open circuit voltage OCV, the battery pack internal resistance, the battery power and the current are calculated through the established electric vehicle power system physical simulation model, and the real-time SOC, the consumed energy, the accumulated ampere-hours and the temperature of the cockpit and the battery are calculated. Finally, the remaining rated capacity of the battery pack is calculated every 60 seconds.

[0115] Step 5: When the cumulative simulation time is greater than the total single-day travel time, enter the single-day charging simulation. When the cumulative stay time is greater than 30 minutes and the SOC is less than 0.8, the power consumed by the heating, ventilation and air-conditioning system and the battery thermal management system, the open circuit voltage OCV, the battery pack internal resistance, the battery power and the current are calculated through the established electric vehicle power system physical simulation model. The real-time SOC, the consumed energy, the cumulative ampere-hours and the temperature of the cockpit and the battery are calculated. Finally, the remaining rated capacity of the battery pack is calculated every 60 seconds.

[0116] After each day's driving data is processed through steps 4 and 5 above, determine whether the cumulative simulation years have reached the user-set simulation years. If not, continue with steps 4 and 5 until the set years are reached. The program automatically stops and outputs the simulation result Excel data in the same file. In the simulation result Excel, users can view the specific data of the electric vehicle battery capacity degradation each day when the brake energy recovery system is turned on.

[0117] Step 6: Open the software platform and, in the file named EV-DOS, set the charger type to "DC_Fast," disable EV regenerative braking, enable the battery pack thermal management system, disable heating, ventilation, and air conditioning, and set the simulation duration to one year. Click Run, and the platform will repeat steps 3 through 5. The program will automatically stop and output the simulation results in an Excel file. In this Excel file, users can view detailed data on the daily battery capacity degradation of the EV while the battery pack thermal management system is enabled.

[0118] Step 7: Open the software platform and, in the file named EV-DOS, set the charger type to "DC_Fast," disable the electric vehicle's brake energy recovery, disable the battery pack thermal management system, enable the heating, ventilation, and air conditioning system, and set the simulation period to one year. Click Run, and the platform will repeat steps 3 through 5. The program will automatically stop and output the simulation results in an Excel file. In this Excel file, users can view detailed data on the daily battery capacity degradation of the electric vehicle while the heating, ventilation, and air conditioning system is enabled.

[0119] After the above steps, a comparison chart of the effects of the brake energy recovery system, heating, ventilation and air conditioning system, and battery thermal management system on battery capacity degradation is obtained one year later. The comparison chart is as follows: Figure 5 The benchmark shown is the result of a run on a driving profile with HVAC turned off, brake energy regeneration turned off, and battery thermal management turned off.

[0120] BTMS_ON is the result of running on a driving profile with only battery thermal management turned on.

[0121] HVAC_ON is the result of running on a driving profile with only the HVAC system turned on.

[0122] RBS_ON is the result of running on a driving profile with only regenerative braking turned on.

[0123] Clearly, the results demonstrate the benefits of BTMS in slowing battery degradation in electric vehicles. Compared to the baseline, when only the battery thermal management system was enabled, the remaining battery capacity increased by 2.57% over a year. However, using only the HVAC system accelerated battery degradation, with a 3.65% degradation over a year. Enabling only brake energy regeneration also helped improve the remaining battery capacity, increasing it by 1.83%. The simulations took less than two hours in total, demonstrating the ability of this platform to simulate the impact of different auxiliary functions on battery life in electric vehicles in a short period of time.

[0124] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A reverse simulation method for dynamic operation of a power system of an electric vehicle, characterized in that: The following steps are involved: Build a physical simulation model of the electric vehicle power system, which includes: Automobile dynamics model, used to calculate the total force acting on the vehicle; The energy transfer model includes an electric vehicle braking energy recovery module, a driving current calculation module, and a driving power calculation model. The electric vehicle braking energy recovery module is used to start and stop braking energy recovery, the driving current calculation module is used to calculate the driving current of the electric vehicle, and the driving power calculation model is used to calculate the driving power of the electric vehicle. Temperature model, including the electric vehicle heating, ventilation and air conditioning system model, the battery thermal management model, the cabin temperature model, and the battery temperature model. The electric vehicle heating, ventilation and air conditioning system model is used to calculate the power consumed by the heating, ventilation and air conditioning system. The battery thermal management model is used to calculate the power required for battery heating or cooling. The cabin temperature model is used to calculate the cabin temperature. The battery temperature model is used to calculate the battery temperature. Battery model, including battery capacity degradation model and battery real-time SOC calculation model. The battery capacity degradation model is used to calculate the battery calendar aging rate and thermal aging rate, thereby calculating the battery capacity degradation. The battery real-time SOC calculation model is used to calculate the battery real-time SOC; The charging model includes a charging judgment module, a charger selection model, and a charging power and charging current model. The charging judgment module is used to calculate the dwell time based on driving data to determine whether there is sufficient time for charging during the day's trip. The charger selection model is used to select car chargers of different power levels. The charging power and charging current model is used to calculate the charging current based on the charging power and charging efficiency. Based on the driving data, the energy transfer of the electric vehicle power system is simulated through the electric vehicle power system physical simulation model to obtain simulation results, which include changes in cabin temperature, battery pack temperature, SOC, and battery capacity degradation.

2. A reverse simulation method for dynamic operation of a power system of an electric vehicle according to claim 1, characterized in that: In the vehicle dynamics model, the formula for calculating the total force acting on the vehicle is: in, The total force required to drive an electric vehicle to move, is the air resistance, is the rolling resistance, is the slope resistance, is the acceleration resistance, , Divided into the energy required to drive the electric vehicle and the total power, is the speed of the electric vehicle, For dragging, For the moment.

3. The reverse simulation method for dynamic operation of a power system of an electric vehicle according to claim 1, characterized in that: In the energy transfer model, the electric vehicle braking energy recovery module is used to start braking energy recovery when the vehicle speed is higher than the preset value and decelerate, and to maintain a constant braking energy recovery efficiency. Recover powertrain energy into the battery system; The formula for calculating the total power of an electric vehicle when it is running is: in, The total power required to drive an electric vehicle is The power consumption of heating, ventilation and air conditioning systems for electric vehicles, is the power consumed by the battery heating system, It is the braking energy recovery power; The formula for calculating the driving current is: in, is the open circuit voltage, is the internal resistance, Input / output current of the battery pack.

4. The method for reverse simulation of dynamic operation of a power system for electric vehicles according to claim 1, characterized in that: In the temperature model, when the electric vehicle is running, the battery temperature is: in is the battery thermal capacity, is the battery temperature, is the ambient temperature, is the cab temperature, 、 、 is the heat transfer coefficient, Heat dissipation / heating energy for the battery pack thermal management system, is the heat energy of the battery pack, , Manage the highest and lowest temperatures for the battery, means or the smallest value among 10, means Or the smallest value among 10; in is the specific heat capacity of the cockpit, is the heat transfer coefficient, Energy consumed by heating, ventilation and air conditioning systems for electric vehicles, 、 is the heat dissipation and heating electric energy coefficient.

5. The method for reverse simulation of dynamic operation of a power system for electric vehicles according to claim 1, characterized in that: In the battery model, the real-time SOC of the electric vehicle is: in, is the initial SOC value of the battery pack, The remaining rated capacity of the battery pack; The remaining capacity of the battery pack, i.e. the battery pack capacity life calculation formula is: in, is the initial capacity of the battery pack, is the thermal aging rate of the battery pack, is the calendar aging rate of the battery pack, Serious factors of battery aging degradation, , , , is the battery aging coefficient, is the activation energy, is the universal gas constant, It is the accumulated ampere-hour.

6. A reverse simulation method for dynamic operation of a power system of an electric vehicle according to any one of claims 1 to 5, characterized in that: In the charger selection model, the types of chargers include: level 1 charging, level 2 charging, DC fast charging, and ultra-fast charging.

7. A reverse simulation platform for the dynamic operation of the power system of electric vehicles, characterized by: The simulation platform collects or simulates real daily driving data and performs reverse simulation using the method described in any one of claims 1-6. The real daily driving data includes: data collection time and its corresponding vehicle speed, road slope, ambient temperature, and vehicle running / stop status. The platform can perform cyclic long-term span simulation based on the above driving data.

8. The reverse simulation platform for dynamic operation of the power system of electric vehicles according to claim 7, characterized in that: The platform allows users to customize vehicle performance and appearance parameters, battery parameters, and charger parameters to simulate vehicles of different sizes and models.

9. The reverse simulation platform for dynamic operation of the power system of electric vehicles according to claim 7, characterized in that: A driving mode configuration can be selected, including: battery thermal management system on / off, heating, ventilation and air conditioning system on / off, and brake energy regeneration system on / off.

10. A reverse simulation platform for dynamic operation of a power system of an electric vehicle according to any one of claims 7 to 9, characterized in that: The platform simulation period can be customized to simulate the degradation of electric vehicle power batteries over a long period of time or even the entire life cycle in a relatively short period of time.

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